Analyzing Airport Reviews on Facebook Using AI

December 1, 2017

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3 m, 41 s

This post is the introduction to a series, in which I use our own cutting-edge text analytics and sentiment analysis software for analyzing airport reviews. By combining qualitative and quantitative data, I’ll tell you which American airports are the lowest- (and highest-) ranked, and why travelers feel the way they do.

A spark of analytical inspiration

At a party this summer, a friend of mine and I were talking about the traveling we do for work, specifically the various hazards and hidden delights of America’s airports. Others at the party overheard us, piping in with their own ideas about which airports were “the best” and which were “a nightmare.” Most folks offered their opinions based on their own anecdotal data.

This discussion stayed with me. Not because I have an obsession with airports or because the party was so boring that airport chat was the highlight of the night. No, what kept the question with me so long was that I knew I could find out the answer. Using data and text analytics, I knew I could use Semantria for analyzing online airport reviews of the biggest airports in the United States. The reports Semantria offers could tell me which ones really are the best and most-liked, and, more importantly, why.

Starting the experiment

While this “shower-thought” might justexit someone else’s mind as quickly as it entered, I decided to run this analysis as an experiment. As a first step, I decided to look at the ten busiest airports in America. I evaluated reviews for airports in Atlanta, New York, Dallas, San Francisco, Phoenix, Las Vegas, Los Angeles, Houston, Denver, and Chicago. Using a sparse data set, I discovered some very interesting things.

Analyzing airport reviews is not a new idea. Likewise, comparing airports based on customer insight is a common practice. But people usually base their analyses on individual subjective opinions, rather than quantifiable data.

In fact, there are hundreds of print and online lists ranking the busiest airports in America. Yet somehow, there’s still no major consensus among these subjective articles as to which airport is considered “best” (though Phoenix Sky Harbor International Airport does often get the top spot). This is a problem of subjectivity. By analyzing airport reviews using a quantitative, objective tool like Semantria, I get a better perspective on why travelers feel the way the do.

Quick insights from analyzing airport reviews

My analysis delivered decisive results. For example, San Francisco rarely makes any of the airport quality listicles. And when it does, it’s often not found in the top ten rankings. Despite this, travelers praise it as one of the finest airports in America. The analysis I ran in Semantria for Excel returned this unexpected result in mere minutes.

In fact, this creates an interesting question. Why is San Francisco’s airport, for example, so well-reviewed by its customers, while the travel industry usually ignores its favorability? On a similar note, why is Phoenix more highly-rated by travel industry reviewers than from the customers themselves? My forthcoming analyses succinctly answer those questions, and more.

Using industry packs for instant configuration

When I first started analyzing airport reviews, I didn’t use the Lexalytics airline industry pack. At first, every analysis I conducted told me that “security” rated positively. This surprised me because, at least in my experience, getting through security at the airport is a miserable process.

But after turning on the airline industry pack configuration, security went from bright green to dark red – that is, the sentiment weight dropped from a net positive to a net negative. Enabling this industry based configuration is as easy as selecting the expiration date for your credit card… you literally pick it from a list. The airline industry pack allows me to see the conversation within the unique context of the airline industry.

Stay tuned for more

In the coming days and weeks I’m going to go alphabetically, airport by airport. When processed through Semantria, this data tells its own story, something deeper and more nuanced than star ratings and editorialized listicles. We’ll use this technology to take a deep dive into the collective voice of a large customer base. What they have to say is interesting, intense, and useful.